Distinguished Engineer, Storage – AI Cloud
Remote • US, CA, Santa Clara
Posted 6d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a Distinguished Engineer to lead the company's storage strategy for AI Cloud, focusing on the Neocloud Provider (NCP) and Cloud Service Provider (CSP) ecosystem. This role involves directing the architecture of high-performance parallel file systems, object stores, and block storage at exabyte scale. You will remain hands-on, collaborating with engineers, SREs, partners, and storage vendors, and leveraging NVIDIA's AI tools to enhance productivity. This is a unique opportunity to shape the storage framework for the AI era at a company that pioneered accelerated computing, ensuring that storage platforms can keep tens of thousands of accelerators continuously busy and power the largest AI workloads worldwide.
Responsibilities
- Lead the multi-year technical plan for AI Cloud Storage expansion across NCPs, defining reference architecture, capabilities, performance, and durability SLOs.
- Serve as the chief storage architect with deep hands-on involvement, leading key reviews and investigating complex production problems.
- Develop prototype reference implementations to minimize risks in new initiatives and make final technical decisions on NCP storage deliveries.
- Define the standard for 'production-ready' in NCP storage, ensuring efficiency, observability, and reduced operational toil.
- Influence GPU delivery by requiring AI Cloud to verify storage-focused ancillary services before accepting GPU capacity.
- Develop and guide architectural direction by working closely with collaborators in training, inference, and accelerated-computing product lines.
- Coordinate with site-reliability, operations, networking, and security colleagues, and align with external cloud providers and storage vendors.
- Develop the open-source path forward for AI storage, establishing and guiding an open-source strategy and engaging with upstream communities.
- Formalize APIs, SDKs, and protocols to enable partners and the industry to build and integrate with NVIDIA at the AI storage level.
- Lead an engineering culture centered on AI tools, using modern AI coding and agentic tools in daily tasks.
- Distribute patterns, prompts, and evaluation harnesses across the storage organization to demonstrate 10x engineering.
- Partner with peer architects to tackle difficult, long-term technical challenges, making automation the primary solution for infrastructure management.
- Design the storage layer for workloads spanning multiple GPU generations, including disaggregated inference and exabyte regional object stores.
- Mentor and develop senior, principal, and distinguished engineers across the storage organization and nearby business units.
- Represent NVIDIA externally in standards bodies, open-source communities, customer briefings, and industry forums.
Requirements
- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- Minimum of 18+ years of practical engineering experience in storage technology.
- Extensive involvement with high-performance parallel file systems (e.g., Lustre, GPFS, WEKA, VAST, BeeGFS, DAOS) at multi-petabyte scale.
- Wide-ranging expertise in object storage (S3/Swift-class) and block storage (NVMe-oF, NVMesh-class, iSCSI).
- Track record of crafting and managing storage platforms at exabyte scale for performance-critical workloads (AI training, HPC, video, hyperscale data lakes).
- Direct responsibility for durability, availability, and performance SLOs measured in 9s.
- Demonstrated ability to set technical strategy across business units and partner organizations.